Director, Data Quality Insights (R-19228)

Hyderabad - IndiaEmployee: Full Timeexecutive

OtherDirector

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Quick Summary

Overview

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate.

Key Responsibilities

The Research & Data Analytics Director is responsible for leading people and operations for Data Quality Insights teams at the assigned site.

Technical Tools

agileci-cddata-analysispeople-managementperformance-management

Shape the Future with Dun & Bradstreet

At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. For over 180 years, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers.

The Role:

The Research & Data Analytics Director is responsible for leading people and operations for Data Quality Insights teams at the assigned site. This role oversees the Accuracy Testing Research and Data Engineering functions while also providing people management and operational leadership for additional onsite Data & Analytics team members.

This position serves as the primary people manager and site‑level leader for Data Quality Insights, ensuring consistent execution, quality discipline, and workforce development across multiple functional roles. The role balances hands‑on operational leadership with broader people management responsibilities, acting as a bridge between frontline supervisors and senior leadership. The role is accountable for workforce performance, cross‑team coordination, operational risk awareness, and alignment to Data Quality Insights priorities, while supporting audit‑defensible outcomes and scalable execution.

People & Site Leadership:

Provide direct people management for Accuracy Testing Research staff, DQI Data Engineers, and other onsite Data & Analytics team members, including coaching, feedback, and performance management.
Ensure consistent application of performance expectations, role clarity, and development standards across onsite teams.
Support hiring, onboarding, training, performance management, and ongoing development of team members to ensure role readiness and sustained performance.
Build a collaborative, inclusive, and high‑accountability team culture aligned with Data Quality Insights values and leadership expectations.
Provide input into promotion readiness, succession planning, and development planning in partnership with senior leadership and HR.

Operational & Execution Oversight:

Lead the DQI Data Engineering team in creation of pipelines, applications and agentic workflows using traditional as well as AI-assisted coding tools
Provide leadership for the Accuracy Testing Manager who oversees the day‑to‑day execution of Accuracy Testing research operations at the site, ensuring work is completed accurately, consistently, and in accordance with documented standards.
Ensure appropriate workload distribution and staffing coverage across research and analytics functions to meet delivery commitments.
Monitor operational indicators such as throughput, backlog, and quality trends, and escalate risks or constraints as needed. Provide requirements for new dashboards to track operations.
Partner with supervisors and senior contributors to ensure high‑risk or high‑judgment work is assigned to appropriately skilled staff.
Support audit preparation, inquiries, and remediation activities related to research and analytics operations.

Quality, Risk & Governance Support:

Ensure adherence to engineering best practices including SDLC and CI/CD testing, deployment and monitoring
Reinforce adherence to documented research instructions, source hierarchies, and documentation standards across teams.
Partner with Quality Control and leadership to identify error trends, calibration needs, and improvement opportunities.
Identify and proactively escalate operational or staffing risks that may impact data integrity, audit outcomes, or delivery timelines.
Ensure consistent application of quality and escalation discipline across all onsite Data Quality Insights functions.

Collaboration & Communication:

Act as the primary site‑level point of contact for Data Quality Insights leadership, providing clear visibility into operational status, risks, and workforce needs.
Coordinate across research, analytics, quality, and leadership teams to support alignment on priorities and execution.
Communicate changes in priorities, expectations, or operating guidance clearly and consistently to onsite teams.
Support cross‑functional collaboration with Product, Technology, or Operations partners as required for site‑level execution.

Bachelor’s degree or equivalent work experience.

Demonstrated experience managing and developing employees across multiple roles or functional areas in research, data quality, analytics, or compliance‑exposed environments.

Strong understanding of quality control concepts, operational risk management, and audit sensitivity.

Proven ability to lead teams with varying skill levels while maintaining consistent performance and accountability standards.

Strong organizational, communication, and prioritization skills, with the ability to balance people leadership and operational execution.

Experience leading data engineers in an Agile environment

Experience with GenAI concepts such as retrieval-augmented generation (RAG), embeddings, prompt design, and model evaluation